Results 101 to 110 of about 8,179,520 (254)
Categorical Features from Question Answers in UK Biobank data fields.
Categorical Features from Question Answers in UK Biobank data fields.
Ruoqing Zhu (724776) +3 more
core +1 more source
Towards a Compositional Framework for Describing Human Phenotypes
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu +11 more
wiley +1 more source
Importance Rheumatoid arthritis (RA), a chronic autoimmune disease linked to higher mortality, benefits from physical activity (PA), which has been shown to reduce disease activity and improve physical function.
Haodong Zheng +6 more
doaj +1 more source
Observed and expected LTC counts in UK Biobank.
The grey bars show the observed LTC counts in UK Biobank. The blue line shows the expected LTC counts in UK Biobank based on the age and sex adjusted regression models fitted in SAIL. The red line shows the expected LTC counts in UK Biobank based on age,
David A. McAllister (9548352) +5 more
core +1 more source
Bulk and genotype‐imputed transcriptomes obscure the cellular drivers of complex disease. CausalCellInfer resolves them by integrating invariant marker selection, deep learning deconvolution, and regularized matrix completion. Applied to ∼500 000 UK Biobank participants across 29 traits, it uncovers hallmark cell‐type proportion shifts, including ...
Liangying Yin +6 more
wiley +1 more source
Background/Aims: Gut–microbiota dysbiosis has been implicated in gallstone formation through alterations in bile acid and cholesterol metabolism, but whether adherence to a microbiota-supportive diet is associated with gallstone disease at the population
Hongyan He, Luohong Li, Xiaoli Yang
doaj +1 more source
Summary statistics of the UK Biobank participants in our sample.
Summary statistics of the UK Biobank participants in our sample.
Tom R. Gaunt (7747922) +4 more
core +1 more source
AI Powered Biobanks From Static Archives to Dynamic Discovery Engines
Large language models (LLMs) provide a potential framework for transforming biobanks from static data repositories into intelligent discovery engines. By enabling unified representation and analysis of multimodal biomedical data, LLM‐based systems facilitate dynamic risk prediction, biomarker identification, and mechanistic interpretation, thereby ...
Wenzhen Yin +5 more
wiley +1 more source
Aims Social determinants of health (SDHs) exert a significant influence on various health outcomes and disparities. This study aimed to explore the associations between combined SDHs and mortality, as well as adverse health outcomes among adults with ...
Xin Qi +11 more
doaj +1 more source
Invitation and recruitment to UK Biobank.
Invitation and recruitment to UK Biobank.
Nick Craddock (170215) +13 more
core +1 more source

